Ask Better Questions About Privacy, Security, and Data Retention

“Enterprise secure” is not an answer. Leaders need a data-flow explanation and evidence covering collection, transmission, storage, access, model use, retention, deletion, incidents, and exit. This decision connects to Build an AI Strategy That Starts With Business Value and Turn Company Priorities Into an AI Opportunity Portfolio, which provide the strategic direction and portfolio context. Use this four-part leadership framework Map data flow — Identify every source, destination, subprocessor, region, log, backup, and user role. Test permissions — Apply least privilege, identity controls, audit logs, review, and removal procedures. Clarify lifecycle — Document retention, deletion, training use, legal holds, export, and contract termination. Prepare response — Define incident notice, investigation, containment, customer communication, and recovery. A practical decision example A team plans to summarize support tickets. Review discovers that pasted data may be retained longer than expected and support staff have broad workspace access. The design changes before customer information enters the tool. This is a hypothetical example; use your own baseline, constraints, and evidence. Evidence, governance, and responsible use Use the NIST AI Risk Management Framework to connect the initiative to governance, context, measurement, and ongoing management. The companion NIST AI RMF Playbook turns those functions into questions leaders can assign and review. The GAO AI Accountability Framework is useful for examining governance, data, performance, and monitoring across the system life cycle. Compare the plan with the OECD AI Principles, particularly transparency, robustness, accountability, and respect for people affected by the system. For generative AI, review the NIST Generative AI Profile and test representative cases using OpenAI’s evaluation guidance. Use the OWASP Top 10 for LLM Applications to discuss application threats before a model can access sensitive information or take actions. Check performance statements against the FTC’s guidance on AI claims, and review information handling with the FTC’s privacy and security resources. For a broader organizational management approach, study the ISO/IEC 42001 overview. Take this to the next leadership meeting Draw the data flow and answer twenty questions across purpose, permission, sensitivity, identity, encryption, logs, retention, deletion, subprocessors, incidents, model training, export, and owner. Record the owner, evidence source, decision date, and what would cause the company to stop. The goal is not to make the document look complete. The goal is to make the next decision explicit, measurable, and accountable. Continue with Prepare an AI Incident Response Plan Before You Need One. Use Run a Quarterly AI Portfolio Review: Keep, Fix, Scale, or Stop to revisit the decision with current evidence.